人工神经网络在煤矿通风机故障诊断中的应用

Application of Artificial Neural Network in Fault Diagnosis of Coal Mine Ventilator

分析了煤矿通风机的常见故障,在介绍BP神经网络原理和算法的基础上,建立了基于BP神经网络模型的通风机故障诊断模型,并应用数学软件MATLAB中的神经网络工具箱实现了通风机不同故障状态的识别。研究结果表明,该方法能准确地诊断通风机的故障类型,具有简单、准确的特点,为实现煤矿通风机的故障预警和保障煤矿的安全生产具有指导意义。

The paper analyzes general fault of coal mine ventilator,fault diagnosis model of ventilator was established based on neural network by introducing theory and algorithm of BP neural network,different fault states of ventilators can be identified by using neural network toolbox of matlab.the results of research show that method can diagnose fault type of ventilators simply and accurately,meanwhile,it is significance to realize fault warning of coal mine ventilators and guarantee safety produce in coal mine.